Nomia
Data Engineer
Salary
Job description
About the Role
As Data Engineer, you will promote data as a key differentiator for Nomia. You will help drive innovation and the building of intelligent systems for internal use, as well as for our customers and suppliers globally. You will be a key member of the team devoted to designing and implementing cutting-edge Agentic solutions.
Roles & Responsibilities
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Design and implement data pipelines for cleaning and enriching data
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Be responsible for the data lake
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Find and curate third-party datasets
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Prepare data for use in experiments
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Design and maintain notebooks to measure the quality and completeness of data
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Understand real-world use cases and translate them into actionable plans
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Conduct experiments to validate design choices or theories
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Create, manage, monitor, and maintain data models
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Design and implement ETL processes
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Document all aspects of your work
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Stay abreast of advancements in data engineering and research new software and techniques
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Participate in code reviews, technical discussions, and cross-functional meetings
About You
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3+ years' experience in data engineering
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Demonstrable experience with Microsoft Azure tools, such as Function Apps and services including Data Factory, Azure Synapse, and Azure Databricks
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Demonstrable experience designing and implementing ETL pipelines
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Proficient in PostgreSQL and T-SQL
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Proficient in Python, with a strong command of data processing libraries such as Pandas and PySpark
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Proficient in the use of Python notebooks
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Experience with event-driven architecture
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Familiarity with LLMs and prompt engineering
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Proficient in writing clean, maintainable code and well-documented data pipelines
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Wide knowledge of different database types and designs
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Familiarity with data modelling techniques
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Genuine enthusiasm for learning new ideas and techniques
General
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Ensure compliance with Nomia's data protection and information security policies
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Hybrid work model — 3 days per week in office, with flexibility based on training or team needs
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Promote inclusivity, innovation, and ethical use of AI across the organisation
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Be adaptable and proactive in learning new tools, techniques, and methods as the AI landscape evolves
